Computational Materials Science: Modeling Materials

Predict and understand materials properties from atomistic simulations with powerful computational chemistry tools in the ADF Modeling Suite. The molecular and periodic DFT, semi-empirical approaches and reactive MD modules are easy to use from the integrated graphical interface so you can study,  at various levels of sophistication, the molecular and bulk properties of systems ranging from a few to a million atoms.

A webinar in 2017 highlighted recent papers and new capabilities for materials modeling (see slides and video), focusing for modeling properties of nanoparticles, batteries, and organic electronics.

ReaxFF Na graphene battery

Key features and benefits:

  • Build clusters, nanotubes, surfaces and bulk (including MOFs & COFs)
  • Visualize PDOS, LDOS, band structures, fat bands, crystal orbitals, QTAIM, potentials, etc.
  • Use same basis sets for molecular and periodic DFT
  • Interface to Quantum ESPRESSO plane wave code
  • Accurate relativistic treatment; all elements; modern xc functionals
  • Proper 2D representation with DFT(B)
  • Insights from bonding analysis, many spectroscopic properties
  • DFTB: electronic parameters for most elements, TD-DFTB
  • ReaxFF: parametrization, event detection, analysis tools
  • Molecule gun: deposit molecules on surfaces (ALD, CVD)
  • Ease of use: same binary and GUI for all codes, scripting tools
Try the Amsterdam Modeling Suite

  Breaking graphene with a fast buckyball bullet  (ReaxFF molecule gun), and then healing it with force biased Monte Carlo (see advanced ReaxFF workshop)